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Biomarkers of environmental benzene exposure.
Author(s) -
Clifford P. Weisel,
Ruilian Yu,
Amit Roy,
Panagiotis Georgopoulos
Publication year - 1996
Publication title -
environmental health perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.257
H-Index - 282
eISSN - 1552-9924
pISSN - 0091-6765
DOI - 10.1289/ehp.961041141
Subject(s) - physiologically based pharmacokinetic modelling , benzene , population , pharmacokinetics , biomarker , environmental chemistry , chemistry , physiology , toxicology , pharmacology , medicine , environmental health , biology , organic chemistry , biochemistry
Environmental exposures to benzene result in increases in body burden that are reflected in various biomarkers of exposure, including benzene in exhaled breath, benzene in blood and urinary trans-trans-muconic acid and S-phenylmercapturic acid. A review of the literature indicates that these biomarkers can be used to distinguish populations with different levels of exposure (such as smokers from nonsmokers and occupationally exposed from environmentally exposed populations) and to determine differences in metabolism. Biomarkers in humans have shown that the percentage of benzene metabolized by the ring-opening pathway is greater at environmental exposures than that at higher occupational exposures, a trend similar to that found in animal studies. This suggests that the dose-response curve is nonlinear; that potential different metabolic mechanisms exist at high and low doses; and that the validity of a linear extrapolation of adverse effects measured at high doses to a population exposed to lower, environmental levels of benzene is uncertain. Time-series measurements of the biomarker, exhaled breath, were used to evaluate a physiologically based pharmacokinetic (PBPK) model. Biases were identified between the PBPK model predictions and experimental data that were adequately described using an empirical compartmental model. It is suggested that a mapping of the PBPK model to a compartmental model can be done to optimize the parameters in the PBPK model to provide a future framework for developing a population physiologically based pharmacokinetic model.

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